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Oracle 1z0-1195-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Create an Autonomous AI Database Serverless instance for a basic workload |
| Working with JSON and Graph in Oracle AI Database | - Explain JSON and Oracle AI Database JSON capabilities - Describe core graph concepts and graph analytic capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
| Building Low-Code Applications and Agentic AI | - Describe Oracle APEX as Oracle's low-code platform - Choose the appropriate Agent Factory capability for a no-code AI agent use case |
| Working with AI and Vector Foundations | - Describe AI, AGI, and machine learning foundations - Explain vectors, embeddings, and the Oracle VECTOR data type - Apply vector distance and indexing concepts to similarity search needs |
| Using Oracle Database Actions and Data Studio Tools | - Describe Database Actions and core development tools - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks |
| Implementing Select AI and AI Vector Search in Autonomous AI Database | - Apply AI Vector Search to combined semantic and business-data search scenarios - Determine how AI Vector Search supports GenAI pipelines and RAG - Describe Select AI in Autonomous AI Database |
Oracle AI Database Foundations Associate Sample Questions:
Question 1
Which output can Select AI deliver to an application?
A. A JSON export file generated from a collection table
B. A result set, a narrative, or the SQL
C. A maintenance recommendation generated from patch history
D. A graph visualization generated from schema relationships
Question 2
A bank wants to identify indirect money movement patterns across several accounts to support fraud investigation. Which approach fits this requirement?
A. Model accounts as vertices and transfers as edges in a property graph
B. Use a relational report that shows one transaction at a time without link analysis
C. Store transaction descriptions as flat text and search by keywords only
D. Store only summary totals for each account without relationship data
Question 3
In a RAG-style application, where does similarity search apply?
A. It replaces the generation step by returning only raw vector values
B. It creates the original source documents from the generated answer
C. It evaluates user authentication rules before retrieving context
D. It retrieves the most relevant stored content for the user's question
Question 4
A data engineer is creating a vector similarity query and wants to choose the distance metric correctly.
Which guidance should be applied?
A. Choose the metric based on the number of rows in the table.
B. Choose the metric based on whether the data also has JSON attributes.
C. Choose the distance metric based on the embedding model that produced the vectors.
D. Choose the metric based on the database maintenance schedule.
Question 5
What does Select AI enable in Autonomous AI Database?
A. Users can ask natural-language questions to get data answers
B. Administrators can provision database instances from natural-language prompts
C. Users can replace every SQL query with graph pattern matching
D. Administrators can rotate customer-managed encryption keys from a query prompt
Solutions:
| Question 1 Answer: B | Question 2 Answer: A | Question 3 Answer: D | Question 4 Answer: C | Question 5 Answer: A |
